The present disclosure relates generally to systems and methods for advertisement planning, and more particularly to systems and methods for forecasting the effectiveness of an advertisement.
Advertisement planning typically includes selecting a number of advertisements based on one or more criteria including the rating of the advertisement. Advertisements, including television, printed, and radio advertisements, are often rated according to their sales effectiveness. The sales effectiveness of an individual advertisement may be determined using one of a number of methods and measuring metrics. For example, the sales effectiveness of an advertisement may be measured by copy testing the advertisement or estimated by a benchmark such as the FAIR SHARE degree-of-difficulty benchmark. However, the sales effectiveness of an advertisement, by itself, provides limited insight to the impact on business results, such as category sales or market share, attributable to the advertisement.
Measurement methods, such as market mix modeling, were developed to determine the contribution to business results attributable to an advertisement or advertisement plan. Such measurement methods determine the advertisement's contribution to business results based on historic data related to the advertisement. Accordingly, current measurement methods, such as market mix modeling, determine an advertisement's contribution to business results subsequent to the publication of the advertisement. However, in many business applications, it is desirable to determine the contribution to business results of an advertisement(s) prior to the publication (i.e., printed publication or airing) of the advertisement(s).